If the 2.5" SSD does not contain a external hard drive enclosure, you can purchase one separate from Amazon.Com, just do a search for "SSD Hard Drive Enclosure"

Assuming you have the SSD and Enclosure,

Attach the 2.5" SSD Hard Drive enclosure to the computer. Most do it through a cable.

If the new 2.5" SSD Hard Drive storage space is larger than your existing hard drive, skip to Step 3. If the If the 2.5" SSD Hard Drive you bought has a smaller storage space than your current Hard Drive, you will need to resize the current drive first before you can begin cloning. You will need to Partition the Mac hard drive so that it is now the same size or smaller of the SSD Hard Drive

First Open Disk Utilities

Then click the hard drive

Change the space of existing hard drive so it's smaller than the new 2.5" SSD Hard Drive

Start the clone

Then Reboot and press Control + R

Select Disk Utilities

Choose the hard drive.

Then Restore

Turn off the Mac

Replace the hard drive

Turn the Macbook over and use a small Phillips screw driver to remove the bottom plate.

If you have issues with TFS being very slow and get the below error message, there could be an issue with the number of items associated with your workspace.

Error Message:

TF401190: The local workspace RAmiscaray;Robert Amiscaray has 101150 items in it, which exceeds the recommended limit of 100000 items. To improve performance, either reduce the number of items in the workspace, or convert the workspace to a server workspace.

Your workspace has to many linked items in TFS.

Solution:

From Visual Studio, choose the slow performing workspace.

Choose the Source Control explorer

Remove project mappings from the slow performing workspace. You may need to do several.

Create a new workspace and add the previously removed project mappings. Repeat.

Amazon SimpleDB is a highly available and flexible non-relational data store that offloads the work of database administration. Developers simply store and query data items via web services requests and Amazon SimpleDB does the rest.

Unbound by the strict requirements of a relational database, Amazon SimpleDB is optimized to provide high availability and flexibility, with little or no administrative burden. Behind the scenes, Amazon SimpleDB creates and manages multiple geographically distributed replicas of your data automatically to enable high availability and data durability. The service charges you only for the resources actually consumed in storing your data and serving your requests. You can change your data model on the fly, and data is automatically indexed for you. With Amazon SimpleDB, you can focus on application development without worrying about infrastructure provisioning, high availability, software maintenance, schema and index management, or performance tuning.

The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance. Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data. Cassandra's support for replicating across multiple datacenters is best-in-class, providing lower latency for your users and the peace of mind of knowing that you can survive regional outages.

Cassandra's data model offers the convenience of column indexes with the performance of log-structured updates, strong support for denormalization and materialized views, and powerful built-in caching.

The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.

Elasticsearch is a highly scalable open-source full-text search and analytics engine. It allows you to store, search, and analyze big volumes of data quickly and in near real time. It is generally used as the underlying engine/technology that powers applications that have complex search features and requirements.

CouchDB is a database that completely embraces the web. Store your data with JSON documents. Access your documents and query your indexes with your web browser, via HTTP. Index, combine, and transform your documents with JavaScript. CouchDB works well with modern web and mobile apps. You can even serve web apps directly out of CouchDB. And you can distribute your data, or your apps, efficiently using CouchDB’s incremental replication. CouchDB supports master-master setups with automatic conflict detection.

RavenDB is a transactional, open-source Document Database written in .NET, and offering a flexible data model designed to address requirements coming from real-world systems. RavenDB allows you to build high-performance, low-latency applications quickly and efficiently.

DynamoDB is a fast, fully managed NoSQL database service that makes it simple and cost-effective to store and retrieve any amount of data, and serve any level of request traffic. Its reliable throughput and single-digit millisecond latency make it a great fit for gaming, ad tech, mobile and many other applications.

Berkeley DB enables the development of custom data management solutions, without the overhead traditionally associated with such custom projects. Berkeley DB provides a collection of well-proven building-block technologies that can be configured to address any application need from the hand-held device to the datacenter, from a local storage solution to a world-wide distributed one, from kilobytes to petabytes.